This paper is in the following e-collection/theme issue:

RCTs - Protocols/Proposals (eHealth) (511) Electronic Health Records (971) Apps, Mobile, Wearables for Diabetes (288) Fitness Trackers and Smart Pedometers/Accelerometers (543)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10009, first published .
Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Authors of this article:

Jing Wang1 Author Orcid Image ;   Deidra Carroll Coleman1 Author Orcid Image ;   Justin Kanter2 Author Orcid Image ;   Brad Ummer3 Author Orcid Image ;   Linda Siminerio4 Author Orcid Image
Article Authors Cited by (18) Tweetations (9) Metrics

Journals

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  2. . An Effective Model of Diabetes Care and Education: Revising the AADE7 Self-Care Behaviors®. The Diabetes Educator 2020;46(2):139 View
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  4. Wang J, Chu C, Li C, Hayes L, Siminerio L. Diabetes Educators’ Insights Regarding Connecting Mobile Phone– and Wearable Tracker–Collected Self-Monitoring Information to a Nationally-Used Electronic Health Record System for Diabetes Education: Descriptive Qualitative Study. JMIR mHealth and uHealth 2018;6(7):e10206 View
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  6. Riddell M, Pooni R, Fontana F, Scott S. Diabetes Technology and Exercise. Endocrinology and Metabolism Clinics of North America 2020;49(1):109 View
  7. Kolb L. An Effective Model of Diabetes Care and Education: The ADCES7 Self-Care Behaviors™. The Science of Diabetes Self-Management and Care 2021;47(1):30 View
  8. Martinez R, Smith B, Etingen B, Houston T, Shimada S, Amante D, Patterson A, Richardson L, Vandenberg G, Cutrona S, Quintiliani L, Frisbee K, Hogan T. Health-Related Goal Setting and Achievement Among Veterans with High Technology Adoption. Journal of General Internal Medicine 2021;36(11):3337 View
  9. Glöggler M, Ammenwerth E. Development and Validation of a Useful Taxonomy of Patient Portals Based on Characteristics of Patient Engagement. Methods of Information in Medicine 2021;60(S 01):e44 View
  10. Kamble A, Desai S, Abhang N. Wearable Activity Trackers: A Structural Investigation into Acceptance and Goal Achievements of Generation Z. American Journal of Health Education 2021;52(5):307 View
  11. Li S, Yin Z, Lesser J, Li C, Choi B, Parra-Medina D, Flores B, Dennis B, Wang J. Community Health Worker-Led mHealth-Enabled Diabetes Self-management Education and Support Intervention in Rural Latino Adults: Single-Arm Feasibility Trial. JMIR Diabetes 2022;7(2):e37534 View
  12. Su Z, Meyer K, Li Y, McDonnell D, Joseph N, Li X, Du Y, Advani S, Cheshmehzangi A, Ahmad J, da Veiga C, Chung R, Wang J, Hao X. Technology-based interventions for nursing home residents: a systematic review protocol. BMJ Open 2021;11(12):e056142 View
  13. Bardram J, Cramer-Petersen C, Maxhuni A, Christensen M, Bækgaard P, Persson D, Lind N, Christensen M, Nørgaard K, Khakurel J, Skinner T, Kownatka D, Jones A. DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. ACM Transactions on Computing for Healthcare 2023;4(2):1 View
  14. Mitchaï P, Mapinduzi J, Verbrugghe J, Michiels S, Janssens L, Kossi O, Bonnechère B, Timmermans A. Mobile technologies for rehabilitation in non-specific spinal disorders: a systematic review of the efficacy and potential for implementation in low- and middle-income countries. European Spine Journal 2023;32(12):4077 View
  15. Chato L, Regentova E. Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data. Journal of Personalized Medicine 2023;13(12):1703 View
  16. Ko J, Wang J, Mbue N, Schembre S, Cron S. Effect of the Implementation of A Multiple-Behavior Self-Monitoring Intervention on Dietary Intake in Type 2 Diabetes (Preprint). JMIR Formative Research 2023 View

Books/Policy Documents

  1. Boland M, Alam F, Bronlund J. Trends in Personalized Nutrition. View
  2. Danquah M, Jeevanandam J. Emerging Nanomedicines for Diabetes Mellitus Theranostics. View